Clinical Data Management Deep Dive: Basics to Advance (2026)

Welcome to the course. In four minutes you will see what clinical data management (CDM) is, who this course is for and how it is organised.

In this lecture

• The three phases every study goes through, and the CDM work in each: start-up, conduct and close-out
• The documents you will learn to write or review: protocol, Data Management Plan, eCRF, edit checks, data transfer agreements, close-out checklists
• The hands-on parts: walkthroughs of two EDC systems (Rave and Veeva) and five labs built on one fictional study

Why it matters on the job

The course is built for people starting their first CDM job and for CRAs, coordinators and nurses moving into data management. Every lecture links back to what you would actually do on a study team.

Practice

Download the CDM Study Brief for the fictional study CCP-HTN-201. It introduces the study, the team and the lab you will do with each lesson. The zip in this lecture holds all 13 study pack files in one download.

What does a clinical data manager actually do all day? This lecture describes the role from the inside: the data you are responsible for, the people you work with and the decisions that are yours to make.

In this lecture

• How the data manager supports a trial from protocol to database lock
• Who you work with: sites, CRAs, the medical lead, biostatisticians, programmers and vendors
• The documents a data manager creates and the ones you review

Why it matters on the job

Hiring managers ask candidates to explain the CDM role in their own words. By the end of this lecture you should be able to do that in two minutes, with examples from each study phase.

Every new medicine goes through four phases of clinical trials before and after approval. This short lecture explains what each phase tests and why the data needs change from one phase to the next.

In this lecture

• Phase I: safety and dose, usually in a small group of healthy volunteers or patients
• Phase II: does it work, and what are the side effects, in a larger patient group
• Phase III: confirming efficacy and safety at scale to support approval; Phase IV: monitoring after the medicine is on the market

Why it matters on the job

The phase sets the size of the study, the number of sites and the amount of data you will manage. A Phase III database looks very different from a Phase I one.

Practice

Take the quiz after this lecture to check you can tell the phases apart.

ICH Good Clinical Practice is the international standard for running trials ethically and producing data regulators can trust. This lecture shows what GCP asks of the data manager specifically.

In this lecture

• The GCP principles that drive CDM work: participant safety, data integrity and traceability
• Your responsibilities across the data lifecycle: collection, validation, queries and database lock
• Common compliance problems and the habits that prevent them

Why it matters on the job

Inspectors check whether every change to the data can be explained. GCP is the reason you document queries, keep audit trails and follow the Data Management Plan.

Practice

The resources include a link to a free GCP certificate course and an interactive module on the regulatory framework.

The 2025 revision of ICH GCP, E6(R3), was written for trials that use digital tools, remote visits and AI. This update lecture explains what changed and what it means for data quality.

In this lecture

• Decentralized trials (DCTs) and digital health technologies, and how they change data collection
• Where AI is being used in clinical research and the safeguards E6(R3) expects
• Why participant protection and data integrity still come first

Why it matters on the job

Sponsors are already running hybrid and remote studies. Knowing the E6(R3) principles helps you ask the right questions when a new data source or tool is proposed.

Clinical research speaks in abbreviations. This lecture goes through the ones you will meet in your first weeks, first the general trial terms and then the ones specific to data management.

In this lecture

• General terms such as AE, SAE, GCP, CRF and RCT
• CDM terms such as EDC, CDASH, SDTM, DMP and UAT
• Simple ways to memorise them

Why it matters on the job

Meetings, emails and SOPs use these terms without explaining them. Knowing them is the fastest way to sound and feel at home on a study team.

Practice

Keep the two abbreviation lists from the resources open while you watch the rest of the course.

Data managers rarely write a document from a blank page. CROs and sponsors keep approved templates, and your job is to make them right for the study. This lecture explains how.

In this lecture

• Where templates come from and why they follow regulatory guidance
• Filling in study-specific information without breaking the approved structure
• Version control, review and checklists

Why it matters on the job

Using the current approved template is often an SOP requirement. An outdated version can mean redoing the work after QA review.

Practice

Take the Document Templates quiz after this lecture.

The protocol is the plan for the whole study, and almost every data decision traces back to it. This lecture walks through how a protocol is developed and where the data manager contributes.

In this lecture

• The steps from first draft through review, finalisation and amendments, following ICH GCP and ISO 14155
• Who writes and reviews it, including the protocol review team
• What the data manager reads it for: visits, assessments, endpoints and timelines

Why it matters on the job

If a visit or assessment is not in the protocol, it should not be in the eCRF. Reading the protocol well is the first skill of a good data manager.

Practice

The CDM Study Brief for CCP-HTN-201 includes the protocol summary used in all five labs. Read the visit schedule and note what is collected at each visit.

The Data Management Plan is the rulebook for a study's data. It says how data will be collected, checked, cleaned, reconciled, locked and archived, and who signs off each step. As a data manager you write it or keep it up to date, and auditors read it to see whether you did what you said you would.

In this lecture

• What a DMP is for and when it is written (start-up, before the database goes live)
• The main sections: data collection, validation and edit checks, external data, quality checks, database lock, archiving
• Who reviews and approves it, and how changes are versioned

Why it matters on the job

Almost every later task in this course points back to the DMP. When a sponsor asks "why did you query this?" or "when is lock?", the answer should already be in the plan.

Practice

Open Data Management Plan v1.0 for the fictional study CCP-HTN-201 (in this lecture's resources). Read section 6 (Data validation) and section 12 (Database lock), then compare them with the blank template. You will use this same plan in the UAT, data cleaning and close-out labs.

Between the final protocol and the first patient, the lead data manager sets up the study. This lecture follows that setup step by step.

In this lecture

• The lead data manager's responsibilities during setup, from CRF development to the move to production
• A timeline of the setup stages: initiation, documentation and database development
• Filing documents, managing data import and export, and who does what

Why it matters on the job

Setup is where most later problems are prevented. A missed form or a wrong specification costs far more to fix after go-live.

Practice

Use Data Management Plan v1.0 from the study pack to see what a finished setup document looks like.

The eCRF is what sites see when they enter data. This lecture shows how an eCRF is designed in Rave, from the protocol to tested, deployed forms.

In this lecture

• Turning the protocol into folders (visits) and forms
• Choosing fields and data types, and applying CDASH and SDTM standards
• Building validations, testing, deployment and ongoing maintenance, using Rave's form builder and global library

Why it matters on the job

A well-designed eCRF prevents errors instead of querying them later. A drop-down list removes a whole class of typing mistakes.

Practice

Open the eCRF Specification v1.0 (Excel) and the Annotated CRF for CCP-HTN-201 to see a complete design for seven forms. Practise these steps in any EDC system you can access, such as a training or sandbox study.

An annotated eCRF shows, for every field, where the value ends up in the submission datasets. This lecture explains CDASH and SDTM and how the annotation connects them.

In this lecture

• CDASH, the standard for collecting data, and SDTM, the standard for submitting it, both from CDISC
• How to annotate an eCRF: mapping each field to its SDTM domain and variable
• Who is involved (data managers, biostatisticians, programmers) and the tools used

Why it matters on the job

Regulators such as the FDA expect submissions in CDISC format. A correct annotated CRF saves the programming team days of guesswork.

Practice

Compare the Annotated CRF for CCP-HTN-201 with the eCRF Specification: every field in the specification has a blue SDTM box in the annotated CRF.

Before a database goes live, the team tests it against its specifications. This lecture explains how UAT is planned, run and documented.

In this lecture

• Screen UAT (do the forms match the specification?) and edit check UAT (does each check fire when it should, and only then?)
• Testing roles and access, test scripts and recording results
• Logging defects, re-testing and filing the results in the eTMF

Why it matters on the job

A check that never fires lets bad data through, and a check that fires on good data floods sites with queries. UAT is your one chance to catch both before go-live.

Practice

Lab 2, Execute the UAT script: run 16 tests against the Edit Check Specification, mark each pass or fail and log the defects. Then take the Lab 2 quiz after the UAT quiz.

eCRF Completion Guidelines tell site staff exactly how to fill in each form. This lecture explains how they are written, reviewed and kept up to date.

In this lecture

• What goes into eCCGs: general rules plus field-by-field instructions
• Who writes, reviews and approves them
• Updating them when the database or protocol changes

Why it matters on the job

Clear guidelines prevent queries. If many sites make the same mistake, the guideline is usually the first thing to fix.

Practice

Read the eCRF Completion Guidelines v1.0 for CCP-HTN-201. Many of the errors you will find in Lab 1 break a rule written there, such as weight in kg.

A CTMS tracks the operational side of a trial: sites, subjects, visits and milestones. Data managers often have no direct access, but they rely on its data constantly.

In this lecture

• What a CTMS does: study setup, site management, subject tracking and reporting
• How CTMS and EDC data connect, and where they should agree
• The reports data managers use from it

Why it matters on the job

When subject counts or visit dates in the EDC do not match the CTMS, someone has to find out why. Knowing what the CTMS holds helps you ask the right person.

Go-live moves the database from the UAT environment to production, where sites enter real data. This lecture covers the checklist and approvals needed first.

In this lecture

• The pre-production checklist: final documents, design review and completed UAT
• System readiness checks and sponsor approval
• Protecting data integrity during and after the move

Why it matters on the job

Once sites start entering data, every change to the build becomes a post-production change, with its own process. Going live too early is expensive.

Once sites start entering data, the data manager's main job is cleaning it: finding values that break the rules, asking the site about them, and closing each question with a clear answer. This lecture covers how queries work in Rave and how to write ones sites can answer quickly.

In this lecture

• System queries (fired by edit checks) and manual queries (raised by you during review)
• How to write a query: state the value, the rule and the request, without telling the site the answer
• Re-queries, query aging and the metrics teams use to track open queries

Why it matters on the job

Data managers never change site data themselves. Your query is the only tool you have, so a vague or leading query costs days.

Practice

Lab 1, Run the edit checks by hand: download the Lab 1 workbook and the Edit Check Specification. Run 18 edit checks on the CCP-HTN-201 listings in Excel, log every finding and write the query. Then take the Lab 1 quiz that follows the Query Management quiz.

Any change to a live database is a post-production change. This lecture explains the request, build, test and release steps that keep live data safe.

In this lecture

• What counts as a PPC and how it is requested and approved
• Building in development, testing (UAT) and moving to production
• Two release methods: a full migration or publishing checks only

Why it matters on the job

A PPC touches data sites have already entered. Good records of what changed, when and why are what an auditor will ask for.

Lab results, ECGs and other vendor data come into the study as files. The Data Transfer Agreement (DTA) fixes what those files contain, how often they arrive and who fixes what when they disagree with the EDC.

In this lecture

• The file specification: variables, formats and naming
• Transfer schedule, secure transfer and a test transfer first
• Security and privacy (ICH GCP, GDPR, HIPAA) and the reconciliation rules

Why it matters on the job

Without a DTA, every vendor file is a surprise. With one, you can check each transfer against an agreed specification.

Practice

Read the Data Transfer Agreement between Meridian Central Lab and Northbridge Clinical (both fictional). Its table of who fixes what is the rulebook for Lab 3.

Some data never passes through the EDC: central lab results, safety database cases, ECG readings. Reconciliation is how you prove the vendor's records and the EDC tell the same story for every subject and visit.

In this lecture

• Preparing for reconciliation: data sources, the transfer agreement and a reconciliation plan
• Matching records on a key (for lab data, the accession number) and listing every difference
• Deciding who fixes what: the site, the vendor, or nobody because it is a true match

Why it matters on the job

Every open difference blocks database lock. A clean reconciliation log, with dates found and resolved, is one of the first things an auditor asks for.

Practice

Lab 3, Reconcile the central-lab file: compare the Meridian lab file with the EDC sample forms and find the differences. Lab 4, SAE reconciliation: compare the safety database with the EDC adverse events. Both workbooks are in this lecture's resources, and each has its own quiz right after this lecture.

Close-out turns live study data into a locked, final dataset. This lecture walks through soft lock, hard lock and what happens after.

In this lecture

• Soft lock: final cleaning, reconciliation, freezing fields and PI sign-off
• Hard lock: final review and approval, removing edit access and extracting the data
• Filing the final documents in the TMF and notifying everyone involved

Why it matters on the job

Lock is the deadline the whole team works towards. A lock that has to be reopened costs the sponsor time and credibility.

Practice

Lab 5, Is the database ready to lock? Review the Database Lock Checklist for CCP-HTN-201 the day before the planned lock and decide whether to recommend lock. Then take the Lab 5 quiz after the Database Closeout quiz.

The Trial Master File holds the documents that prove a trial was run properly. This lecture shows how it is managed in Veeva Vault.

In this lecture

• What belongs in the TMF and how it is organised
• Veeva Vault features: a central repository, workflows and access control
• Filing correctly: classification, metadata and staying inspection-ready

Why it matters on the job

Data management documents (DMP, UAT results, lock approvals) must be filed in the TMF. If they are not there, inspectors treat the work as not done.

The kick-off meeting starts the working relationship between the sponsor, the CRO and the vendors. This lecture shows how a data manager prepares for it and follows up.

In this lecture

• Preparing: reviewing the protocol and checking systems are ready
• What to raise: the data management approach, vendors, timelines and risks
• Following up on actions after the meeting

Why it matters on the job

Decisions made at kick-off shape the whole study. A data manager who comes prepared gets problems settled early.

A Quality Finish Camp (QFC) meeting is held near the end of a study to plan the path to database lock. This lecture walks through a typical agenda.

In this lecture

• Status of data management documents and open queries
• Vendor data transfers and SAE reconciliation
• Lock timelines and risks, such as late data entry or slow sponsor review

Why it matters on the job

The QFC is where the lock date is confirmed or moved. Arriving with accurate numbers on open items is the data manager's main contribution.

Practice

The slides can be adapted for your own study. The Database Lock Checklist from Lab 5 is a good companion.

Before a sponsor awards a study, shortlisted CROs present their proposal at a bid defense. This lecture explains how it works and what data management brings to it.

In this lecture

• What the sponsor's Request for Proposal (RfP) should contain: timelines, draft protocol, specifications, assumptions and key questions
• What the CRO shows: its experience and the team who would run the study
• How a data manager can answer questions on timelines and data approach

Why it matters on the job

Being asked to join a bid defense is a sign of trust. Knowing the format helps you contribute with confidence.

This lecture lays out the data management timeline for a study from start-up to database lock, with the tasks, owners and milestones at each stage.

In this lecture

• Start-up tasks: eCRF setup and edit check programming
• Conduct tasks: data entry, cleaning, coding and reconciliation
• Close-out tasks and the lock milestones, and who owns each step

Why it matters on the job

Sponsors judge data management on dates met. Knowing which task depends on which helps you see a delay coming.

Practice

The DM blueprint timeline in the resources can be used as a starting point for your own project plan.

This lecture turns the course into a job search plan: where data managers work, how to present your skills and how to prepare for interviews.

In this lecture

• The kinds of employers that hire data managers: pharmaceutical companies, biotech firms and CROs
• Building a CV that shows CDM skills, with a sample to adapt
• Common interview questions, general and CDM-specific

Why it matters on the job

Interviewers often ask candidates to walk through a task. The labs in this course (edit checks, UAT, reconciliation, lock readiness) give you real examples to talk about.

Practice

Download the CRO list, the sample CV and the two interview question documents from the resources.